Heuristic Search System Using Precomputed Data Districts
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Solution Overview
Problem
Conventional search engines face challenges in returning relevant results due to the sheer volume of data, as they rely on keyword or key phrase matching and proprietary algorithms that may not accurately reflect user-specific relevance, often resulting in useless or irrelevant search results.
Innovation Solution
The system employs a heuristic approach by using a Unique Identifier operator in URIs to directly retrieve resources that are pre-tagged or labeled by the server authority, allowing users to specify resource identifiers that correspond to meaningful categories, thereby bypassing traditional keyword-based searches and improving the relevance of search results.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If conventional keyword-based search algorithms are used, then the search engine can process vast amounts of data, but the relevance and usefulness of the returned results deteriorate
Solution Approach 1:
The patent segments the search process into two distinct phases: (1) a pre-computation phase where the server authority creates a structured map of data districts, categories, and relationships before any user search, and (2) a query phase where the user's keyword search is rapidly matched against this pre-organized structure. This segmentation allows the system to handle large data volumes efficiently while returning highly relevant results, as the heavy computational work of organizing data is done once in advance rather than repeatedly during each search.
Solution Approach 2:
The server authority performs preliminary actions by pre-computing and storing a comprehensive map of the database structure, including data districts, categories, sub-categories, and inter-resource relationships, before any user search occurs. This pre-computation includes establishing the hierarchical structure and computing relevance metrics in advance. When a user searches, the system simply queries this pre-prepared structure, enabling rapid retrieval of relevant results without performing complex calculations during the actual search operation.
2Extent of automation
If proprietary relevance algorithms are employed to rank results, then the search engine can automate result ordering, but the accuracy of user-specific relevance determination worsens
Solution Approach 1:
The patent introduces an intermediary structured map that sits between the raw database contents and the user search results. This map, created and maintained by the server authority, serves as a mediator that translates user keywords into precise locations within the database structure. The map includes pre-computed relationships, categories, and relevance information that bridge the gap between automated processing and user-specific needs, enabling the system to return results that are both automatically ordered and highly relevant to the user's specific query intent.
3Quantity of substance
If the system returns all possible hits for a keyword search, then the search engine provides comprehensive coverage, but the time required for the user to find relevant information increases
Solution Approach 1:
The patent extracts only the most relevant results from the complete set of possible matches by using the pre-computed structured map. Instead of returning all hits that contain the search keywords, the system queries the map to identify and extract only those resources that are most highly relevant to the user's query, based on pre-established relationships, categories, and relevance metrics. This extraction process significantly reduces the number of results the user must review while maintaining comprehensive coverage of truly relevant information.
4Ease of manufacture
If keyword-based searching is used, then the search process is simple to implement, but the ability to retrieve pre-defined information districts deteriorates
Solution Approach 1:
The patent implements a dynamic search system that adapts to the user's query while maintaining simplicity. The structured map allows the system to dynamically adjust the search strategy based on the keywords provided, automatically navigating through the pre-defined data districts and categories to retrieve the most relevant results. The system dynamically combines keyword matching with the pre-computed structural relationships, enabling it to both maintain ease of use and precisely retrieve specific information districts without requiring complex user input or system configuration.
Data Source
AI summary
A method of retrieval of items of particular relevance from a particular domain. A processor receives from a remote computing device a resource-identifying string that has a combination of a predefined notation and a resource-related sub-string. The processor uses the resource-identifying string to retrieve a subset of data items from within a data set, the subset of data items relating to a subset of resources within a set of resources available to be served by the particular domain over a distributed network. The processor uses the subset of data items to generate a list of the subset of resources and serves the list to the remote computing device.